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Applied Ai Engineer Jobs in Arizona (NOW HIRING)

YO AI Labs

AI Data Science Expert - Remote

Phoenix, AZ · Remote

$100 - $200/hr

Prompt Engineering * AI Output Evaluation * Quality Assurance * Technical Documentation * Technical ... Applied AI, Statistics, Quantitative Analytics, or Data Analytics. * Experience producing or ...

YO AI Labs

AI Data Scientist Expert - Remote

Phoenix, AZ · Remote

$100 - $200/hr

Prompt Engineering * AI Output Evaluation * Quality Assurance * Technical Documentation * Technical ... Applied AI, Statistics, Quantitative Analytics, or Data Analytics. * Experience producing or ...

Axosoft, LLC

Applied Data Scientist

Scottsdale, AZ · On-site

Help shape how GitKraken uses AI and data to improve developer workflows, team velocity, and ... Deep experience in machine learning, applied AI, or a similarly hands-on product data role at a ...

Axosoft, LLC

Applied Data Scientist

Scottsdale, AZ · On-site

Help shape how GitKraken uses AI and data to improve developer workflows, team velocity, and ... Deep experience in machine learning, applied AI, or a similarly hands-on product data role at a ...

Prologis

Senior AI Applied Engineer

Phoenix, AZ · On-site

$125K - $186K/yr

Senior AI Applied Engineer Company: Prologis A day in the life In this role, you will explore and experiment with emerging AI techniques to establish new and evolve existing enterprise AI patterns.

Equity Methods

Staff Software Engineer

Scottsdale, AZ · On-site

This is a senior individual contributor role for an engineer who thrives at the intersection of financial services domain expertise and applied AI engineering. You will work directly alongside our ...

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All JobsApplied Ai Engineer JobsApplied Ai Engineer Jobs in Arizona

Applied Ai Engineer information

What are the key skills and qualifications needed to thrive as an applied AI engineer?

To thrive as an Applied AI Engineer, you need strong proficiency in programming (especially Python), machine learning algorithms, statistics, and a relevant degree in computer science or a related field. Familiarity with frameworks like TensorFlow or PyTorch, experience with cloud platforms (such as AWS or Azure), and knowledge of data management tools are typically required. Excellent problem-solving, communication, and teamwork skills help you translate complex models into real-world solutions and collaborate across disciplines. These competencies ensure you can effectively develop, deploy, and maintain AI systems that drive business value.

What are some common challenges applied AI engineers face when deploying AI models into production environments?

Applied AI Engineers often encounter challenges such as ensuring models perform consistently on real-world data, optimizing models for speed and scalability, and integrating AI solutions with existing systems. Managing data privacy, monitoring for model drift, and maintaining robust documentation are also key concerns. Collaboration with DevOps, data engineering, and product teams is essential to address these challenges effectively and deliver reliable AI-driven solutions.

What is the difference between Applied Ai Engineer vs Data Scientist?

AspectApplied Ai EngineerData Scientist
Required CredentialsBachelor's or Master's in CS, AI, or related fields; experience with AI frameworksBachelor's or Master's in CS, Statistics, or related fields; strong analytical skills
Work EnvironmentDevelops and deploys AI models in production environmentsAnalyzes data to extract insights and build predictive models
Industry UsageUsed in tech, healthcare, finance for deploying AI solutionsUsed across industries for data analysis and modeling

Applied Ai Engineers focus on implementing and deploying AI models in real-world applications, while Data Scientists primarily analyze data to generate insights and build predictive models. Both roles require similar educational backgrounds but differ in their core responsibilities and work environments.

How much does an applied AI engineer make?

An applied AI engineer's salary varies based on experience, location, and industry, but typically ranges from $80,000 to $150,000 annually. Senior roles or those with specialized skills in machine learning, deep learning, and programming languages like Python or TensorFlow tend to earn higher salaries.

What does an applied AI engineer do?

An applied AI engineer develops and implements artificial intelligence models and algorithms to solve real-world problems. They work with data, machine learning frameworks, and programming languages like Python or TensorFlow to create practical AI solutions for businesses or products.

What are popular job titles related to Applied Ai Engineer jobs in Arizona?

For Applied Ai Engineer jobs in Arizona, the most frequently searched job titles are:

What job categories do people searching Applied Ai Engineer jobs in Arizona look for?

The top searched job categories for Applied Ai Engineer jobs in Arizona are:

What cities in Arizona are hiring for Applied Ai Engineer jobs?

Cities in Arizona with the most Applied Ai Engineer job openings:

Applied Ai Engineer jobs near you
Infographic showing various Applied Ai Engineer job openings in Arizona as of August 2026, with employment types broken down into 76% Full Time, 21% Part Time, and 3% Contract. Highlights an 66% Physical, 4% Hybrid, and 30% Remote job distribution.

AI Data Science Expert - Remote

YO AI Labs

Phoenix, AZ • Remote

$100 - $200/hr

Part-time

Posted 27 days ago

Job description

Job Title: AI Data Science Domain Expert

Job Type: Contractor (Part-Time)
Location: Remote

Job Overview

We are seeking experienced AI Data Science Domain Experts to contribute their expertise to an innovative project focused on advancing next-generation AI systems. In this role, you will review, evaluate, and refine AI-generated technical and analytical content to improve model accuracy, reasoning, and overall performance. No prior AI experience is required—your data science expertise, analytical thinking, and communication skills are what matter most.

Key Responsibilities
  • Review, edit, and refine AI-generated content for accuracy, clarity, and technical relevance.
  • Develop, optimize, and evaluate prompts to improve AI model performance.
  • Conduct rubric-based assessments of AI outputs and provide structured feedback.
  • Perform independent research and fact-checking to validate technical information.
  • Annotate data and support quality assurance initiatives for AI training.
  • Interpret complex datasets and prepare clear technical reports and summaries.
  • Collaborate remotely with project teams to improve AI models and workflows.
Required Skills
  • Critical Thinking
  • Analytical Reasoning
  • Prompt Engineering
  • AI Output Evaluation
  • Quality Assurance
  • Technical Documentation
  • Technical & Report Writing
  • Content Review & Editing
  • Data Annotation
  • Data Interpretation
  • Fact Checking
  • Independent Research
  • Problem-Solving
  • Attention to Detail
Preferred Qualifications
  • 3+ years of experience in Data Science, Machine Learning, Applied AI, Statistics, Quantitative Analytics, or Data Analytics.
  • Experience producing or reviewing research papers, analytical reports, technical documentation, experiment summaries, or data-driven recommendations.
  • Strong analytical reasoning, critical thinking, and written communication skills.
  • Experience with data annotation, content review, or rubric-based evaluation is preferred.
  • Familiarity with prompt engineering, AI output evaluation, fact-checking, or RLHF is a plus.
  • Master's, MBA, PhD, or other advanced degree is preferred.